한국작물학회지 (KOREAN JOURNAL OF CROP SCIENCE)

  • 제67권4호
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  • Pages.274-284
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  • 2022
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  • 0252-9777(pISSN)
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  • 2287-8432(eISSN)
한국작물학회 (The Korean Society of Crop Science)
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드론 영상을 이용한 케나프(Hibiscus cannabinus L.) 작물 높이의 노지 표현형 분석

Field Phenotyping of Plant Height in Kenaf (Hibiscus cannabinus L.) using UAV Imagery

  • 장규진 (서울대학교 바이오시스템공학과) ;
  • 김재영 (국립농업과학원 농업생명자원부 유전자공학과) ;
  • 김동욱 (서울대학교 바이오시스템공학과) ;
  • 정용석 (제주대학교 식물자원환경전공) ;
  • 김학진 (서울대학교 바이오시스템공학과)
  • Gyujin Jang (Department of Biosystems Engineering, Seoul National University) ;
  • Jaeyoung Kim (Gene Engineering Division, National Institute of Agricultural Sciences, Rural Development Administraion) ;
  • Dongwook Kim (Department of Biosystems Engineering, Seoul National University) ;
  • Yong Suk Chung (Deparement of Plant Resources and Environment, Jeju National University) ;
  • Hak-Jin Kim (Department of Biosystems Engineering, Seoul National University)
  • 투고 : 2022.10.17
  • 심사 : 2022.11.10
  • 발행 : 2022.12.01
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초록

국내 환경에 적합한 케나프 육종을 위해선 비용, 정확도, 속도가 최적으로 설계된 정량적인 고속탐색법(high-throughput)에 기반한 표현형 분석법이 필요하다. 최근 UAV 기반의 원격탐사 기법의 발달로 노지에서 재배되는 작물의 생육인자들에 대한 대량 데이터를 저비용으로 신속하게 얻을 수 있으며 정확하게 분석하기 위한 연구가 활발하게 진행되고 있다. 본 연구에서는 국내에서 요구되는 케나프의 섬유와 가축 사료로서 육종을 위해 해당 목적과 부합한 케나프 높이를 주요 표현형 인자로 선정하여 UAV-RGB에 SfM 알고리즘 기반의 사진 측량 기술을 적용함으로 높이를 예측하고자 하였다. 기존 방법으로 예측한 작물 높이는 바람에 의한 작물의 흔들림으로 오차가 발생할 수 있으며 키가 2 m 이상 크게 자라 실측도 어려운 문제가 있다. 이러한 문제점을 해결하고자 바람에 흔들리지 않는 일정 높이를 가지는 고정 구조물을 설치하여 기준점을 이용한 모델식으로 기하 보정을 통해 높이 예측성능을 개선하였다. 그 결과 R2는 0.80으로 나타났으며, 보정 전(R2 = 0.80, slope = 0.87, offset = -2.51) 보다 높은 신뢰성(R2 = 0.80, slope = 0.94, offset = -1.62)을 확보하였다. 품종별로 생육단계에 따라 측정한 높이 지도를 통해 얻어진 케나프 키 정보는 품종 별로 유의미한 차이를 보임으로서 해당 방법으로 예측한 케나프 높이가 섬유와 가축 사료 목적의 육종 선발에 활용될 수 있을 것으로 판단하였다.

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R2) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

키워드

과제정보

본 논문은 제주대학교 친환경농업연구소(Sustainable Agriculture Research Institute, SARI)의 시험 포장 제공 등과 농림식품기술기획평가원 연구사업(세부과제번호: 322032031WT011)의 지원에 이루어졌으며, 이에 감사드립니다.

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